A cluster-based key agreement scheme using keyed hashing for Body Area Networks

  • Authors:
  • Aftab Ali;Sarah Irum;Firdous Kausar;Farrukh Aslam Khan

  • Affiliations:
  • Department of Computer Science, National University of Computer & Emerging Sciences, Islamabad, Pakistan;Department of Computer Science, National University of Computer & Emerging Sciences, Islamabad, Pakistan;Department of Computer Science, National University of Computer & Emerging Sciences, Islamabad, Pakistan;Department of Computer Science, National University of Computer & Emerging Sciences, Islamabad, Pakistan

  • Venue:
  • Multimedia Tools and Applications
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

In recent years, Body Area Networks (BANs) have gained immense popularity in the domain of healthcare as well as monitoring of soldiers in the battlefield. Security of a BAN is inevitable as we secure the lives of soldiers and patients. In this paper, we propose a security framework using Keyed-Hashing Message Authentication Code (HMAC-MD5) to protect the personal information in a BAN. We assume a network in which nodes sense physiological variables such as electrocardiography (EKG), electroencephalography (EEG), pulse oximeter data, blood pressure and cardiac output. Heterogeneous wireless sensor network is considered which consists of a powerful High-end sensor (H-sensor) and several Low-end sensors (L-sensors). EKG is used for secure communication between nodes as it introduces plug and play capability in BANs. The process is made secure by applying HMAC-MD5 on EKG blocks. Key agreement is done by comparing HMAC of feature blocks between sensors resulting in a more secure network. The analysis is done by calculating the entropy of keys and checking the randomness of EKG data using NIST-randomness testing suite.